The present invention relates broadly to signal processing systems, and more particularly to a system for extracting a threshold value of interest, such as the median value, from a set of data values.
Many of the electronic data processors of today are required to monitor selected physical parameters of a defined system to provide feedback data required for the supervisory and/or automatic control of the defined system. In some cases, these defined systems must be controlled in real time whereby the feedback data must be monitored in relation to time. These monitored parameters may be a pressure, a temperature, or even an optical image, but are generally not electrical in nature unless dealing with an electrical power system, for example. Therefore, a transducer is normally provided to transform the physical measurement into an analog electrical representation thereof which is ultimately adapted for use by the data processor. Unfortunately, the environment surrounding the transducer is not always suitable to provide an ideal measurement of the physical parameter of interest. Usually, some undesirable background clutter is included with the desired parameter measurement and the composite signal may provide a false electrical representation of the system parameter to the data processor. For this reason, many of the feedback time related data signals are filtered by the data processor in an attempt to segregate the desired signal from the unwanted background clutter signals normally included therewith.
In one particular type of data processor which is primarily used for video or infrared imaging, statistical methods are employed to enhance the electrical signal representative of the desired target optical image and suppress any undesirable electrical signals representing background clutter images found therewith. One approach used for this type of system is to extract a median electrical amplitude value from the set of electrical amplitude values which constitute the image or portion thereof viewed by the optoelectronic transducer of the imaging system. The imaging system produces a substantial image of the target by blanking all the electrical amplitude values less than the median value. This type of statistical filtering approach may also be applied to other data processors related to temperature and pressure control, for example.
Most of the electronic data processors which include statistical methods for filtering input data signals, similar to the one just described, perform their operations digitally. The function involved in extracting the median value from a set of incoming data values may be implemented with a variety of digital counters and logic circuits, and the operation performed thereby is generally in sequential order. In some instances, one median extractor may be time shared with many signals for the purposes of statistically filtering each signal using the median value extracted therefrom. It is evident that an electronic data processor incorporating many monitored signals will spend a great deal of its processing time filtering each signal if a common median extractor is used in a time shared mode. On the other hand, if a median extractor of conventional design is incorporated into each data signal input channel to reduce the processing time for filtering each channel, the data processor would become overly burdened with hardware, not to mention the excessive costs involved and reliability aspects.
From the above discussion, it appears that there exists a need for a simple device for extracting various threshold values including the median from a set of input data values. Accordingly, such a device that could be implemented with large-scale-integration circuit technology to reduce the amount of hardware conventionally required and be capable of performing extraction operations concurrent with other operations of the data processor to reduce the amount of processing time required overall would certainly be desirable.